Antenna Season Report Notebook¶

Josh Dillon, Last Revised January 2022

This notebook examines an individual antenna's performance over a whole season. This notebook parses information from each nightly rtp_summarynotebook (as saved to .csvs) and builds a table describing antenna performance. It also reproduces per-antenna plots from each auto_metrics notebook pertinent to the specific antenna.

In [1]:
import os
from IPython.display import display, HTML
display(HTML("<style>.container { width:100% !important; }</style>"))
In [2]:
# If you want to run this notebook locally, copy the output of the next cell into the next line of this cell.
# antenna = "004"
# csv_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/_rtp_summary_'
# auto_metrics_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/auto_metrics_inspect'
# os.environ["ANTENNA"] = antenna
# os.environ["CSV_FOLDER"] = csv_folder
# os.environ["AUTO_METRICS_FOLDER"] = auto_metrics_folder
In [3]:
# Use environment variables to figure out path to the csvs and auto_metrics
antenna = str(int(os.environ["ANTENNA"]))
csv_folder = os.environ["CSV_FOLDER"]
auto_metrics_folder = os.environ["AUTO_METRICS_FOLDER"]
print(f'antenna = "{antenna}"')
print(f'csv_folder = "{csv_folder}"')
print(f'auto_metrics_folder = "{auto_metrics_folder}"')

antenna = "96"
csv_folder = "/home/obs/src/H6C_Notebooks/_rtp_summary_"
auto_metrics_folder = "/home/obs/src/H6C_Notebooks/auto_metrics_inspect"
In [4]:
display(HTML(f'<h1 style=font-size:50px><u>Antenna {antenna} Report</u><p></p></h1>'))

Antenna 96 Report

In [5]:
import numpy as np
import pandas as pd
pd.set_option('display.max_rows', 1000)
import glob
import re
from hera_notebook_templates.utils import status_colors, Antenna
In [6]:
# load csvs and auto_metrics htmls in reverse chronological order
csvs = sorted(glob.glob(os.path.join(csv_folder, 'rtp_summary_table*.csv')))[::-1]
print(f'Found {len(csvs)} csvs in {csv_folder}')
auto_metric_htmls = sorted(glob.glob(auto_metrics_folder + '/auto_metrics_inspect_*.html'))[::-1]
print(f'Found {len(auto_metric_htmls)} auto_metrics notebooks in {auto_metrics_folder}')

Found 85 csvs in /home/obs/src/H6C_Notebooks/_rtp_summary_
Found 83 auto_metrics notebooks in /home/obs/src/H6C_Notebooks/auto_metrics_inspect
In [7]:
# Per-season options
mean_round_modz_cut = 4
dead_cut = 0.4
crossed_cut = 0.0

def jd_to_summary_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/_rtp_summary_/rtp_summary_{jd}.html'

def jd_to_auto_metrics_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/auto_metrics_inspect/auto_metrics_inspect_{jd}.html'

Load relevant info from summary CSVs¶

In [8]:
this_antenna = None
jds = []

# parse information about antennas and nodes
for csv in csvs:
    df = pd.read_csv(csv)
    for n in range(len(df)):
        # Add this day to the antenna
        row = df.loc[n]
        if isinstance(row['Ant'], str) and '<a href' in row['Ant']:
            antnum = int(row['Ant'].split('</a>')[0].split('>')[-1]) # it's a link, extract antnum
        else:
            antnum = int(row['Ant'])
        if antnum != int(antenna):
            continue
        
        if np.issubdtype(type(row['Node']), np.integer):
            row['Node'] = str(row['Node'])
        if type(row['Node']) == str and row['Node'].isnumeric():
            row['Node'] = 'N' + ('0' if len(row['Node']) == 1 else '') + row['Node']
            
        if this_antenna is None:
            this_antenna = Antenna(row['Ant'], row['Node'])
        jd = [int(s) for s in re.split('_|\.', csv) if s.isdigit()][-1]
        jds.append(jd)
        this_antenna.add_day(jd, row)
        break
In [9]:
# build dataframe
to_show = {'JDs': [f'<a href="{jd_to_summary_url(jd)}" target="_blank">{jd}</a>' for jd in jds]}
to_show['A Priori Status'] = [this_antenna.statuses[jd] for jd in jds]

df = pd.DataFrame(to_show)

# create bar chart columns for flagging percentages:
bar_cols = {}
bar_cols['Auto Metrics Flags'] = [this_antenna.auto_flags[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jee)'] = [this_antenna.dead_flags_Jee[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jnn)'] = [this_antenna.dead_flags_Jnn[jd] for jd in jds]
bar_cols['Crossed Fraction in Ant Metrics'] = [this_antenna.crossed_flags[jd] for jd in jds]
bar_cols['Flag Fraction Before Redcal'] = [this_antenna.flags_before_redcal[jd] for jd in jds]
bar_cols['Flagged By Redcal chi^2 Fraction'] = [this_antenna.redcal_flags[jd] for jd in jds]
for col in bar_cols:
    df[col] = bar_cols[col]

z_score_cols = {}
z_score_cols['ee Shape Modified Z-Score'] = [this_antenna.ee_shape_zs[jd] for jd in jds]
z_score_cols['nn Shape Modified Z-Score'] = [this_antenna.nn_shape_zs[jd] for jd in jds]
z_score_cols['ee Power Modified Z-Score'] = [this_antenna.ee_power_zs[jd] for jd in jds]
z_score_cols['nn Power Modified Z-Score'] = [this_antenna.nn_power_zs[jd] for jd in jds]
z_score_cols['ee Temporal Variability Modified Z-Score'] = [this_antenna.ee_temp_var_zs[jd] for jd in jds]
z_score_cols['nn Temporal Variability Modified Z-Score'] = [this_antenna.nn_temp_var_zs[jd] for jd in jds]
z_score_cols['ee Temporal Discontinuties Modified Z-Score'] = [this_antenna.ee_temp_discon_zs[jd] for jd in jds]
z_score_cols['nn Temporal Discontinuties Modified Z-Score'] = [this_antenna.nn_temp_discon_zs[jd] for jd in jds]
for col in z_score_cols:
    df[col] = z_score_cols[col]

ant_metrics_cols = {}
ant_metrics_cols['Average Dead Ant Metric (Jee)'] = [this_antenna.Jee_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Dead Ant Metric (Jnn)'] = [this_antenna.Jnn_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Crossed Ant Metric'] = [this_antenna.crossed_metrics[jd] for jd in jds]
for col in ant_metrics_cols:
    df[col] = ant_metrics_cols[col]

redcal_cols = {}
redcal_cols['Median chi^2 Per Antenna (Jee)'] = [this_antenna.Jee_chisqs[jd] for jd in jds]
redcal_cols['Median chi^2 Per Antenna (Jnn)'] = [this_antenna.Jnn_chisqs[jd] for jd in jds]   
for col in redcal_cols:
    df[col] = redcal_cols[col]

# style dataframe
table = df.style.hide_index()\
          .applymap(lambda val: f'background-color: {status_colors[val]}' if val in status_colors else '', subset=['A Priori Status']) \
          .background_gradient(cmap='viridis', vmax=mean_round_modz_cut * 3, vmin=0, axis=None, subset=list(z_score_cols.keys())) \
          .background_gradient(cmap='bwr_r', vmin=dead_cut-.25, vmax=dead_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .background_gradient(cmap='bwr_r', vmin=crossed_cut-.25, vmax=crossed_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .background_gradient(cmap='plasma', vmax=4, vmin=1, axis=None, subset=list(redcal_cols.keys())) \
          .applymap(lambda val: 'font-weight: bold' if val < dead_cut else '', subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val < crossed_cut else '', subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .applymap(lambda val: 'color: red' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .bar(subset=list(bar_cols.keys()), vmin=0, vmax=1) \
          .format({col: '{:,.4f}'.format for col in z_score_cols}) \
          .format({col: '{:,.4f}'.format for col in ant_metrics_cols}) \
          .format('{:,.2%}', na_rep='-', subset=list(bar_cols.keys())) \
          .set_table_styles([dict(selector="th",props=[('max-width', f'70pt')])])

Table 1: Per-Night RTP Summary Info For This Atenna¶

This table reproduces each night's row for this antenna from the RTP Summary notebooks. For more info on the columns, see those notebooks, linked in the JD column.

In [10]:
display(HTML(f'<h2>Antenna {antenna}, Node {this_antenna.node}:</h2>'))
HTML(table.render(render_links=True, escape=False))

Antenna 96, Node N11:

Out[10]:
JDs A Priori Status Auto Metrics Flags Dead Fraction in Ant Metrics (Jee) Dead Fraction in Ant Metrics (Jnn) Crossed Fraction in Ant Metrics Flag Fraction Before Redcal Flagged By Redcal chi^2 Fraction ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score Average Dead Ant Metric (Jee) Average Dead Ant Metric (Jnn) Average Crossed Ant Metric Median chi^2 Per Antenna (Jee) Median chi^2 Per Antenna (Jnn)
2459902 not_connected 100.00% 100.00% 100.00% 0.00% - - 13.259240 14.511034 4.281508 4.816718 7.653540 8.125085 1.167687 0.713364 0.0336 0.0388 0.0028 nan nan
2459901 not_connected 100.00% 100.00% 100.00% 0.00% - - 13.471894 14.804430 3.786298 4.455034 6.966945 7.050396 0.952165 0.660702 0.0346 0.0401 0.0031 nan nan
2459900 not_connected 100.00% 100.00% 100.00% 0.00% - - 12.173595 15.002830 4.112304 4.860751 8.828788 7.537154 0.912528 0.677679 0.0332 0.0376 0.0025 nan nan
2459898 not_connected 100.00% 100.00% 100.00% 0.00% - - 10.795932 12.267520 3.689842 4.400274 8.135603 9.290660 1.729075 1.281220 0.0334 0.0374 0.0023 nan nan
2459897 not_connected 100.00% 100.00% 100.00% 0.00% - - 10.539000 12.005516 3.652359 4.567762 9.333257 9.916151 1.596088 1.181670 0.0327 0.0359 0.0020 nan nan
2459896 not_connected 100.00% 100.00% 100.00% 0.00% - - 10.817262 12.160234 3.943635 4.650980 9.842981 10.939186 1.030514 0.562768 0.0328 0.0369 0.0026 nan nan
2459895 not_connected 100.00% 100.00% 100.00% 0.00% - - 13.545036 14.879020 5.117509 5.608208 10.089610 10.954293 6.003742 5.504951 0.0332 0.0372 0.0024 nan nan
2459894 not_connected 100.00% 100.00% 100.00% 0.00% - - 12.484432 14.201007 3.215940 4.025216 9.689490 10.480626 1.752637 1.046720 0.0336 0.0377 0.0025 nan nan
2459893 not_connected 100.00% 100.00% 100.00% 0.00% - - 12.801532 14.667101 3.612315 4.409731 8.113070 9.241227 2.339425 1.324367 0.0334 0.0378 0.0025 nan nan
2459892 not_connected 100.00% 100.00% 100.00% 0.00% - - 12.892225 14.470662 4.294542 5.070174 6.494966 6.995694 1.507390 1.081061 0.0345 0.0406 0.0036 nan nan
2459891 not_connected 100.00% 100.00% 100.00% 0.00% - - 11.453154 13.309214 4.079719 5.018698 8.476806 10.355044 1.374451 0.947056 0.0331 0.0375 0.0026 nan nan
2459890 not_connected 100.00% 100.00% 100.00% 0.00% - - 12.116427 13.534661 5.093932 5.757802 8.070383 9.070402 0.564484 0.050829 0.0328 0.0365 0.0021 nan nan
2459889 not_connected 100.00% 100.00% 100.00% 0.00% - - 13.428615 15.343470 3.787374 4.731767 10.951766 12.870452 2.245391 1.449873 0.0339 0.0387 0.0027 nan nan
2459888 not_connected 100.00% 100.00% 100.00% 0.00% - - 11.262846 12.782140 4.905098 5.592845 9.857036 11.804934 2.172085 2.073689 0.0336 0.0388 0.0030 nan nan
2459887 not_connected 100.00% 100.00% 100.00% 0.00% - - 12.010018 13.686997 5.062053 5.498809 7.381857 10.310278 0.915824 0.780509 0.0338 0.0388 0.0029 nan nan
2459886 not_connected 100.00% 100.00% 100.00% 0.00% - - 16.928945 18.538846 4.545587 5.033995 6.443787 8.089331 2.562999 2.029831 0.0352 0.0418 0.0037 nan nan
2459885 not_connected 100.00% 100.00% 100.00% 0.00% - - 20.631144 22.392025 24.945492 26.703802 14.248975 19.496402 17.206890 12.013107 0.0334 0.0376 0.0023 nan nan
2459884 not_connected 100.00% 100.00% 100.00% 0.00% - - 11.481932 12.862059 4.710346 5.348999 7.949514 9.933694 0.924988 0.405680 0.0329 0.0391 0.0043 nan nan
2459883 not_connected 100.00% 100.00% 100.00% 0.00% - - 16.082947 17.898514 23.068877 24.466636 7.855841 10.852847 3.691600 2.882901 0.0334 0.0420 0.0055 nan nan
2459882 not_connected 100.00% 100.00% 100.00% 0.00% - - 26.813255 29.225252 24.655558 26.770205 11.135148 15.250633 1.627256 1.261407 0.0344 0.0398 0.0036 nan nan
2459881 not_connected 100.00% 100.00% 100.00% 0.00% - - 15.139161 16.672265 28.559713 30.666963 21.997548 30.518098 6.357405 13.820961 0.0330 0.0401 0.0049 nan nan
2459880 not_connected 100.00% 100.00% 100.00% 0.00% - - 18.376234 20.278631 24.191615 25.456623 6.719644 9.262487 1.652108 0.787989 0.0330 0.0400 0.0047 nan nan
2459879 not_connected 100.00% 100.00% 100.00% 0.00% - - 9.647505 10.884125 4.322650 4.896789 1.367276 2.034150 1.907303 1.322151 0.0329 0.0393 0.0044 nan nan
2459878 not_connected 100.00% 100.00% 100.00% 0.00% - - 16.524218 18.114469 29.353530 30.783257 11.505065 15.753377 5.413207 3.532721 0.0352 0.0429 0.0049 nan nan

Load antenna metric spectra and waterfalls from auto_metrics notebooks.¶

In [11]:
htmls_to_display = []
for am_html in auto_metric_htmls:
    html_to_display = ''
    # read html into a list of lines
    with open(am_html) as f:
        lines = f.readlines()
    
    # find section with this antenna's metric plots and add to html_to_display
    jd = [int(s) for s in re.split('_|\.', am_html) if s.isdigit()][-1]
    try:
        section_start_line = lines.index(f'<h2>Antenna {antenna}: {jd}</h2>\n')
    except ValueError:
        continue
    html_to_display += lines[section_start_line].replace(str(jd), f'<a href="{jd_to_auto_metrics_url(jd)}" target="_blank">{jd}</a>')
    for line in lines[section_start_line + 1:]:
        html_to_display += line
        if '<hr' in line:
            htmls_to_display.append(html_to_display)
            break

Figure 1: Antenna autocorrelation metric spectra and waterfalls.¶

These figures are reproduced from auto_metrics notebooks. For more info on the specific plots and metrics, see those notebooks (linked at the JD). The most recent 100 days (at most) are shown.

In [12]:
for i, html_to_display in enumerate(htmls_to_display):
    if i == 100:
        break
    display(HTML(html_to_display))

Antenna 96: 2459902

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
96 N11 not_connected nn Shape 14.511034 13.259240 14.511034 4.281508 4.816718 7.653540 8.125085 1.167687 0.713364

Antenna 96: 2459901

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
96 N11 not_connected nn Shape 14.804430 13.471894 14.804430 3.786298 4.455034 6.966945 7.050396 0.952165 0.660702

Antenna 96: 2459900

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
96 N11 not_connected nn Shape 15.002830 12.173595 15.002830 4.112304 4.860751 8.828788 7.537154 0.912528 0.677679

Antenna 96: 2459898

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
96 N11 not_connected nn Shape 12.267520 12.267520 10.795932 4.400274 3.689842 9.290660 8.135603 1.281220 1.729075

Antenna 96: 2459897

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
96 N11 not_connected nn Shape 12.005516 12.005516 10.539000 4.567762 3.652359 9.916151 9.333257 1.181670 1.596088

Antenna 96: 2459896

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
96 N11 not_connected nn Shape 12.160234 12.160234 10.817262 4.650980 3.943635 10.939186 9.842981 0.562768 1.030514

Antenna 96: 2459895

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
96 N11 not_connected nn Shape 14.879020 13.545036 14.879020 5.117509 5.608208 10.089610 10.954293 6.003742 5.504951

Antenna 96: 2459894

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
96 N11 not_connected nn Shape 14.201007 14.201007 12.484432 4.025216 3.215940 10.480626 9.689490 1.046720 1.752637

Antenna 96: 2459893

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
96 N11 not_connected nn Shape 14.667101 12.801532 14.667101 3.612315 4.409731 8.113070 9.241227 2.339425 1.324367

Antenna 96: 2459892

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
96 N11 not_connected nn Shape 14.470662 14.470662 12.892225 5.070174 4.294542 6.995694 6.494966 1.081061 1.507390

Antenna 96: 2459891

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
96 N11 not_connected nn Shape 13.309214 11.453154 13.309214 4.079719 5.018698 8.476806 10.355044 1.374451 0.947056

Antenna 96: 2459890

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
96 N11 not_connected nn Shape 13.534661 13.534661 12.116427 5.757802 5.093932 9.070402 8.070383 0.050829 0.564484

Antenna 96: 2459889

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
96 N11 not_connected nn Shape 15.343470 13.428615 15.343470 3.787374 4.731767 10.951766 12.870452 2.245391 1.449873

Antenna 96: 2459888

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
96 N11 not_connected nn Shape 12.782140 12.782140 11.262846 5.592845 4.905098 11.804934 9.857036 2.073689 2.172085

Antenna 96: 2459887

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
96 N11 not_connected nn Shape 13.686997 13.686997 12.010018 5.498809 5.062053 10.310278 7.381857 0.780509 0.915824

Antenna 96: 2459886

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
96 N11 not_connected nn Shape 18.538846 16.928945 18.538846 4.545587 5.033995 6.443787 8.089331 2.562999 2.029831

Antenna 96: 2459885

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
96 N11 not_connected nn Power 26.703802 22.392025 20.631144 26.703802 24.945492 19.496402 14.248975 12.013107 17.206890

Antenna 96: 2459884

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
96 N11 not_connected nn Shape 12.862059 12.862059 11.481932 5.348999 4.710346 9.933694 7.949514 0.405680 0.924988

Antenna 96: 2459883

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
96 N11 not_connected nn Power 24.466636 17.898514 16.082947 24.466636 23.068877 10.852847 7.855841 2.882901 3.691600

Antenna 96: 2459882

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
96 N11 not_connected nn Shape 29.225252 29.225252 26.813255 26.770205 24.655558 15.250633 11.135148 1.261407 1.627256

Antenna 96: 2459881

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
96 N11 not_connected nn Power 30.666963 16.672265 15.139161 30.666963 28.559713 30.518098 21.997548 13.820961 6.357405

Antenna 96: 2459880

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
96 N11 not_connected nn Power 25.456623 20.278631 18.376234 25.456623 24.191615 9.262487 6.719644 0.787989 1.652108

Antenna 96: 2459879

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
96 N11 not_connected nn Shape 10.884125 10.884125 9.647505 4.896789 4.322650 2.034150 1.367276 1.322151 1.907303

Antenna 96: 2459878

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
96 N11 not_connected nn Power 30.783257 18.114469 16.524218 30.783257 29.353530 15.753377 11.505065 3.532721 5.413207
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